Navigation of Multiple Kinematically Constrained Robots

Loizou, Savvas G.; Kyriakopoulos, Kostas J.

doi:10.1109/tro.2007.912092

Cited by 78 publications

(65 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…(23), the angular velocity is directly controlled by the wheels rotation. It is worth highlighting that the framework allows integration of other kinds of kinematic constraints by changing the ω t model accordingly, such as the Ackerman type, Campion et al [28], and Macek et al [33]; synchronised type Fox et al [29]; differential drive Song and Chang [32]; or the platforms studied by Loizou and Kyriakopolous [30]. The approach to infer x t and x t+1 is by quantifying the wheels angular displacement directly by the speed drivers.…”

Section: Position Modelmentioning

confidence: 99%

“…Charifa and Bikdash [23] compared the behaviour of several variants of artificial potential function methods with emphasis on the quality of path geometry, and velocity and acceleration profiles. Loizou and Kyriakopolous [30] proposed a kinematic framework for modelling mobility of multiple robots that mathematically combines heterogeneous locomotion constraints for control of the system.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exponential Fields Formulation for WMR Navigation

Martínez‐García

Torres-Cordoba

2012

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

Abstract. In this manuscript, an autonomous navigation algorithm for wheeled mobile robots (WMR) operating in dynamic environments (indoors or structured outdoors) is formulated. The planning scheme is of critical importance for autonomous navigational tasks in complex dynamic environments. In fast dynamic environments, path planning needs algorithms able to sense simultaneously a diversity of obstacles, and use such sensory information to improve real-time navigation control, while moving towards a desired goal destination. The framework tackles 4 issues: 1) Reformulation of the Social Force Model (SFM) adapted to WMR; 2) the cohesion of a general inertial scheme to represents motion in any coordinate system; 3) control of actuators rotational speed as a general model regardless kinematic restrictions; 4) assuming detection of features (obstacles/goals), adaptive numeric weights are formulated to affect navigational exponential components. Simulation and experimental outdoors results are presented to show the feasibility of the proposed framework.

show abstract

Section: Position Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exponential Fields Formulation for WMR Navigation

Martínez‐García

Torres-Cordoba

2012

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

show abstract

“…Recently, spring/dump models [9]- [11] have been proposed to overcome the rigidity of the original virtual structures approaches [12], [13]. In such models, the robots are connected using virtual joints that allow the structure to be temporarily modified by external forces (e.g.…”

Section: A Related Workmentioning

confidence: 99%

Follow-the-leader formation marching through a scalable O(log<inf>2</inf>n) Parallel Architecture.

Colorado

Barrientos

Rossi

et al. 2010

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

View full text Add to dashboard Cite

. Although several works have addressed such problem, little attention has been devoted to study the computational complexity within the framework of large-scale systems. This paper presents our current work on how to achieve high computational performance for systems composed by a large number of robots that must fulfill with a marching and formation task. A scalable Multi-Processor Parallel Architecture is introduced with the purpose of achieving scalability, i.e., computation time of O(log 2 n) for a n-robots system. Our architecture has been tested onto a multi-processor system and validated against several simulations testing.

show abstract

“…In [19], the authors combined a collision-free PPM with a back-stepping controller and applied it to a dynamic model of a multiple robot navigation function to a team of holonomic and nonholonomic mobile robots. However, they assumed that the environment is known and stationary.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Obstacle Avoidance for a Swarm of Autonomous Mobile Robots

Hedjar

Bounkhel

2014

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

In this paper, we propose a computational trajectory generation algorithm for swarm mobile robots using local information in a dynamic environment. The algorithm plans a reference path based on constrained convex nonlinear optimization which avoids both static and dynamic obstacles. This algorithm is combined with one-step-ahead predictive control for a swarm of mobile robots to track the generated paths and reach the goals without collision. The numerical simulations and experimental results demonstrate the effectiveness of the proposed free-collision path planning algorithm.

show abstract

Navigation of Multiple Kinematically Constrained Robots

Cited by 78 publications

References 34 publications

Exponential Fields Formulation for WMR Navigation

Exponential Fields Formulation for WMR Navigation

Follow-the-leader formation marching through a scalable O(log<inf>2</inf>n) Parallel Architecture.

Real-Time Obstacle Avoidance for a Swarm of Autonomous Mobile Robots

Contact Info

Product

Resources

About